Top variables that correlate with Popularity of the first name Jeff

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Data source: US Social Security Administration
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Popularity of the first name Jeff correlates with...

Variable	Correlation	Years	Has img?
Cottage cheese consumption	r=0.95	32yrs	No

Popularity of the first name Jeff also correlates with...

Variable	Correlation	Years	Sys. Score
Kerosene used in Turkiye	r=0.96	43yrs	432
Kerosene used in Mexico	r=0.95	40yrs	427
Gasoline pumped in Latvia	r=0.95	31yrs	418
Burglaries in Michigan	r=0.96	38yrs	416
Burglaries in Oregon	r=0.96	38yrs	416
Burglaries in Colorado	r=0.96	38yrs	416
Remaining Forest Cover in the Brazilian Amazon	r=0.92	36yrs	396
GMO use in cotton	r=0.96	23yrs	396
The number of conveyor operators in New Jersey	r=0.97	20yrs	392
The number of data entry keyers in Ohio	r=0.97	20yrs	392
The number of postal service machine operators in Oregon	r=0.97	20yrs	392
Portion of all US dairy skim-solids allocated to the production of fluid beverage milk	r=0.96	22yrs	389
US average milk-fat content of milk fat and skim solids byproduct fluid beverage milk	r=0.95	22yrs	388
Burglaries in Texas	r=0.95	38yrs	384
US birth rates of triplets or more	r=0.94	20yrs	384
The divorce rate in North Carolina	r=0.95	23yrs	383
The marriage rate in Idaho	r=0.95	23yrs	382
The marriage rate in Wyoming	r=0.95	23yrs	382
Physical album shipment volume in the United States	r=0.93	24yrs	380
U.S. intercountry adoptions	r=0.94	23yrs	380
GMO use in cotton in Texas	r=0.96	23yrs	376
Cigarette Smoking Rate for US adults	r=0.92	21yrs	375
Google searches for 'desktop background'	r=0.94	16yrs	374
United States music album sales	r=0.94	16yrs	373
Petroluem consumption in Bulgaria	r=0.93	42yrs	366
Air pollution in New York City	r=0.94	43yrs	366
Air pollution in Los Angeles	r=0.93	43yrs	364
Burglary rates in the US	r=0.94	38yrs	362
The number of postal service machine operators in Vermont	r=0.97	20yrs	362
Air pollution in Los Angeles	r=0.91	43yrs	362
Lloyds Banking Group's stock price (LYG)	r=0.87	21yrs	358
US household spending on clothing	r=0.92	23yrs	357
US household spending on clothin for women	r=0.92	23yrs	357
Gasoline pumped in Bulgaria	r=0.93	42yrs	356
Average number of milk cows in the United States	r=0.89	43yrs	356
The number of payroll and timekeeping clerks in Wisconsin	r=0.97	20yrs	352
The divorce rate in Kentucky	r=0.94	23yrs	352
Arson in United States	r=0.92	38yrs	350
Kerosene used in Norway	r=0.92	43yrs	346
The divorce rate in Wyoming	r=0.94	23yrs	342
The number of switchboard operators in Alabama	r=0.96	20yrs	340
Milk consumption	r=0.94	32yrs	338
Kerosene used in United States	r=0.92	43yrs	336
Air pollution in New York City	r=0.91	43yrs	332
The number of file clerks in Arkansas	r=0.96	20yrs	330
The divorce rate in Arkansas	r=0.93	23yrs	330
Robberies in Michigan	r=0.95	38yrs	324
Kerosene used in Hong Kong	r=0.91	42yrs	323
The number of prepress technicians and workers in Arkansas	r=0.96	20yrs	320
Air pollution in Manchester, New Hampshire	r=0.92	43yrs	320
The divorce rate in Alabama	r=0.92	23yrs	318
Kerosene used in Romania	r=0.91	42yrs	313
Burglaries in Oklahoma	r=0.94	38yrs	312
The number of telemarketers in California	r=0.95	20yrs	310
Air pollution in San Diego, California	r=0.92	43yrs	310
The divorce rate in Florida	r=0.92	23yrs	308
Kerosene used in Uruguay	r=0.91	42yrs	303
Burglaries in Washington	r=0.94	38yrs	302
The number of data entry keyers in Connecticut	r=0.96	20yrs	300
Air pollution in Spokane, Washington	r=0.92	43yrs	300
The divorce rate in Mississippi	r=0.92	23yrs	298
Burglaries in California	r=0.94	38yrs	292
The number of proofreaders in Connecticut	r=0.96	20yrs	290
Air pollution in Oxnard, California	r=0.92	41yrs	288
The marriage rate in Alabama	r=0.92	23yrs	287
Burglaries in Florida	r=0.93	38yrs	281
The number of postal service machine operators in Idaho	r=0.96	20yrs	280
The marriage rate in Alaska	r=0.92	23yrs	277
Air pollution in San Diego, California	r=0.9	43yrs	277
Geothermal power generated in Austria	r=0.93	17yrs	274
Burglaries in Nevada	r=0.93	38yrs	271
The number of cooks, institution and cafeteria in Louisiana	r=0.96	20yrs	270
The marriage rate in Nevada	r=0.92	23yrs	267
Liquefied petroleum gas used in Greenland	r=0.92	22yrs	264
Burglaries in Arizona	r=0.93	38yrs	261
The number of bill collectors in Maryland	r=0.95	20yrs	260
The marriage rate in Arkansas	r=0.91	23yrs	256
Burglaries in New York	r=0.93	38yrs	251
The number of file clerks in Massachusetts	r=0.96	20yrs	250
The marriage rate in Louisiana	r=0.91	23yrs	246
Gasoline pumped in Kosovo	r=0.92	14yrs	246
Burglaries in Virginia	r=0.93	38yrs	241
The number of data entry keyers in Minnesota	r=0.96	20yrs	240
The divorce rate in Texas	r=0.9	23yrs	236
Kerosene used in Portugal	r=0.9	43yrs	232
Motor vehicle thefts in Massachusetts	r=0.93	38yrs	231
The number of postal service machine operators in Nebraska	r=0.96	20yrs	230
The divorce rate in Virginia	r=0.9	23yrs	226
The number of typists in New Jersey	r=0.96	20yrs	220
Burglaries in Minnesota	r=0.92	38yrs	220
Kerosene used in Bolivia	r=0.89	42yrs	220
The number of postal service machine operators in New Mexico	r=0.96	20yrs	210
Burglaries in New Mexico	r=0.92	38yrs	210
Kerosene used in Brazil	r=0.89	42yrs	210
The number of computer programmers in New York	r=0.95	20yrs	200
Burglaries in Rhode Island	r=0.92	38yrs	200
Kerosene used in Ecuador	r=0.88	42yrs	198
Burglaries in Connecticut	r=0.92	38yrs	190
Petroluem consumption in Romania	r=0.88	42yrs	188
Gasoline pumped in Somalia	r=0.87	42yrs	177

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^{What is Sys. Score?} You caught me! While it would be intuitive to sort only by "correlation," I have a big, weird database. If I sort only by correlation, often all the top results are from some one or two very large datasets (like the weather or labor statistics), and it overwhelms the page.

I can't show you *all* the correlations, because my database would get too large and this page would take a very long time to load. Instead I opt to show you a subset, and I sort them by a magic system score. It starts with the correlation, but penalizes variables that repeat from the same dataset. (It also gives a bonus to variables I happen to find interesting.)


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